Introduction
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R is one of the most widely used data mining tools in scientific and business applications, among dozens of commercial and open-source data mining software. It is free and expandable with over 3,600 packages. However, it is not easy for beginners to find appropriate packages or functions to use for their data mining tasks. It is more difficult, even for experienced users, to work out the optimal combination of multiple packages or functions to solve their business problems and the best way to use them in the data mining process of their applications. This book aims to facilitate using R in data mining applications by presenting real-world applications in various areas.

Objective
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This book will present around 20 applications on data mining with R. Each application is to be presented as one chapter, covering its background, business problems, data extraction and exploration, data preprocessing, modeling, model evaluation, findings and model deployment. In this way, it will help readers to learn to solve real-world problems with a set of data mining techniques and then apply the techniques and methodologies in their own data mining projects. Code examples and sample data will be provided, so that readers can easily learn the techniques by running the codes by themselves.

Target audience
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The audience includes data miners, analysts and R users from industry, and university students and researchers who are interested in data mining with R.

Submission procedure
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The book is now open for a second round of chapter proposals, with a due date of 31 May 2012. Potential authors are expected to submit a 1-2 page manuscript proposal clearly explaining the mission and concerns of the proposed chapter. Full chapters are due by 31 July 2012. All submitted chapters will be reviewed by 2 or 3 reviewers. Please submit your chapter proposals and full chapters at https://www.easychair.org/account/signin.cgi?conf=dmar2013.